Abstract Hearing aids are able to restore some hearing abilities for people with auditory impairments, but background noise remains a significant problem. Unfortunately, very little is understood about how speech is encoded in the auditory system, particularly in impaired systems with prosthetic amplifiers. A better understanding of the effects of hearing aids on speech coding in noise could lead to new insights for the design of these devices. There is growing evidence that across-fiber neural coding is important for speech perception, but there is no research that relates spatiotemporal coding and hearing aid amplification. The goal of the proposed research is to characterize how hearing aids affect vowel coding in noise at the level of the auditory nerve, and to evaluate a novel hearing aid solution that is designed to enhance across- fiber coding. The strength of rate-place, temporal-place, and spatiotemporal coding schemes will be compared in quiet and in the presence of background noise. The general hypothesis guiding the proposed work is that, although current frequency-dependent gain strategies do not improve spatiotemporal coding, novel amplification techniques based on physiological phase effects can improve spatiotemporal coding. The effects of two hearing aid algorithms on vowel coding in noise (relative to normal and impaired) will be quantified: a linear hearing aid algorithm and a multichannel wide-dynamic-range compression algorithm. In addition, the ability of all-pass filters to enhance impaired spatiotemporal patterns will be evaluated. Two phase-correction algorithms are proposed: one with all-pass filters centered on the formants of a vowel, and another with all-pass filters centered on each harmonic component. The proposed neurophysiological experiments will provide valuable data about the effects of hearing aid amplification on auditory nerve coding of vowels in noise. These data will be useful for understanding the effects of amplification and designing hearing aids that allow patients to better understand speech in noise.